Natural Hazards

, Volume 57, Issue 2, pp 167–184 | Cite as

Forecasting groundwater level fluctuations for rainfall-induced landslide

  • Yao-Ming Hong
  • Shiuan Wan
Original Paper


Groundwater plays a critical and important role in many landslides. Heavy precipitation can raise the groundwater level within a hillslope and lead to instability. The purpose of this paper is to present a model by means of continuity equation to predict groundwater level fluctuations in hillslope in response to hourly precipitation rates. The linear reservoir method is employed to describe the travel time distribution of infiltration, and Darcy’s law is then used to establish the groundwater flux rate of control volume. The governing equation shows that the changing rate of groundwater level fluctuation can be interpreted by two new defined variables (Sink Number and Rise Number) in this study. The application of the model is demonstrated using the rainfall-induced landslide at Lu-Shan, Nantou County, Taiwan. Data from one storm event are used to calibrate the model and estimate parameters by using the heuristic algorithm. Post-storm rainfall data from another storm event are employed to verify the calibrated parameters. The contribution of this study shows that a small Sink Number results in a fast recession and a large Rise Number yields a fast rise of groundwater level. This method may be practical to have better understanding on the rainfall-induced landslide.


Groundwater level fluctuation Hillslope Linear reservoir method Rainfall-induced landslide 


  1. Abbasov RK, Mahmudov RN (2009) Analysis of non-climatic origins of floods in the downstream part of the Kura River, Azerbaijan. Nat Hazards 50:235–248CrossRefGoogle Scholar
  2. Anderson MP, Woessner WW (1992) Applied groundwater modeling, simulation of flow and advective transport. Academic Press, San DiegoGoogle Scholar
  3. Bhark EW, Small EE (2003) Association between plant canopies and the spatial patterns of infiltration in shrubland and grassland of the Chihuahuan Desert, New Mexico. Ecosystems 6:185–196CrossRefGoogle Scholar
  4. Caris JPT, van Asch TWJ (1991) Geophysical, geotechnical and hydrological investigations of a small landslide in the French Alps. Eng Geol 31(3–4):249–276Google Scholar
  5. Chapra SC, Canale RP (1988) Numerical methods for engineers, 2nd edn. McGraw-Hill, New York, pp 453–455Google Scholar
  6. Chow VT, Maidment DR, Mays LW (1988) Applied hydrology. McGraw-Hill, Singapore, pp 242–264Google Scholar
  7. Gattinoni P (2009) Parametrical landslide modeling for the hydrogeological susceptibility assessment: from the Crati Valley to the Cavallerizzo landslide (Southern Italy). Nat Hazards 50:161–178CrossRefGoogle Scholar
  8. Gelhar LW, Wilson JL (1974) Ground-water quality modeling. Groundwater 12:399–408Google Scholar
  9. Hong YM (2008) Graphical estimation of detention pond volume for rainfall of short duration. J Hydro Environ Res 2:109–117CrossRefGoogle Scholar
  10. Hunt RJ, Prudic DE, Walker JF, Anderson MP (2008) Importance of unsaturated zone flow for simulating recharge in a humid climate. Ground Water 46(4):551–560CrossRefGoogle Scholar
  11. Lee LJE, Lawrence DSL, Price M (2006) Analysis of water-level response to rainfall and implications for recharge pathways in the Chalk aquifer, SE England. J Hydrol 330:604–620CrossRefGoogle Scholar
  12. Li AG, Yue ZQ, Tham LG, Lee CF (2005) Field-monitored variations of soil moisture and matric suction in a saprolite slope. Can Geotech J 42:13–26CrossRefGoogle Scholar
  13. Malet JP, Laigle D, Remaıˆtre A, Maquaire O (2005) Triggering conditions and mobility of debris flows associated to complex earthflows. Geomorphology 66:215–235CrossRefGoogle Scholar
  14. Mantovani F, Pasuto A, Silvano S, Zannoni A (2000) Collecting data to define future hazard scenarios of the Tessina landslide. Int J Appl Earth Observation Geoinformation 2(1):33–40CrossRefGoogle Scholar
  15. Maréchal JC, Dewandel B, Ahmed S, Galeazzi L, Zaidi FK (2006) Combined estimation of specific yield and natural recharge in a semi-arid groundwater basin with irrigated agriculture. J Hydrol 329:281–293CrossRefGoogle Scholar
  16. McDonald MG, Harbaugh AW (2003) The history of MODFLOW. Ground Water 41:280–283CrossRefGoogle Scholar
  17. Neaupane KM, Achet SH (2004) Use of backpropagation neural network for landslide monitoring: a case study in the higher Himalaya. Eng Geol 74:213–226CrossRefGoogle Scholar
  18. Park E, Parker JC (2008) A simple model for water table fluctuations in response to precipitation. J Hydrol 356:344–349CrossRefGoogle Scholar
  19. Pulido-Velazquez MA, Sahuquillo-Herraiz A, Ochoa-Rivera JC, Pulido-Velazquez D (2005) Modeling of stream–aquifer interaction: the embedded multireservoir model. J Hydrol 313:166–181CrossRefGoogle Scholar
  20. Rasmussen WC, Andreasen GE (1959) Hydrologic budget of the beaverdam creek basin, Maryland. US Geological Survey Water-Supply Paper 1472, 106Google Scholar
  21. Ray RL, Jacobs JM (2007) Relationships among remotely sensed soil moisture, precipitation and landslide events. Nat Hazards 43:211–222CrossRefGoogle Scholar
  22. Rushton KR, Redshaw SC (1979) Seepage and groundwater flow, 339. Wiley, ChichesterGoogle Scholar
  23. Schmidt J, Dikau R (2004) Modeling historical climate variability and slope stability. Geomorphology 60:433–447CrossRefGoogle Scholar
  24. Schwartz BF, Schreiber ME (2009) Quantifying potential recharge in mantled sinkholes using ERT. Ground Water. doi: 10.1111/j.1745-6584.2008.00505.x
  25. Sophocleous M (1991) Combining the soil water balance and water level fluctuation method to estimate natural groundwater recharge: practical aspects. J Hydrol 124:229–241CrossRefGoogle Scholar
  26. State of florida department of transportation (2004) Stormwater management facility handbook. 69–70Google Scholar
  27. Szilagyi J, Harvey FE, Ayers JA (2005) Regional estimation of total recharge to ground water in Nebraska. Ground Water 43(1):63–69CrossRefGoogle Scholar
  28. Trigo RM, Zˆezere JL, Rodrigues ML, Trigo IF (2005) The influence of the North Atlantic Oscillation on rainfall triggering of landslides near Lisbon. Nat Hazards 36:331–354CrossRefGoogle Scholar
  29. U. S. Geological Survey (2009) Access 15 Jan 2009
  30. Van Asch ThWJ, Buma J, Van Beek LPH (1999) A view on some hydrological triggering systems in landslides. Geomorphology 30:25–32CrossRefGoogle Scholar
  31. Wu J, Zhang R, Yang J (1996) Analysis of Precipitation-recharge relationships. J Hydrol 177:143–160CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of Design for Sustainable EnvironmentMingDao UniversityPeetow, ChanghuaTaiwan, R.O.C
  2. 2.Department of Information ManagementLing Tung UniversityTaichungTaiwan

Personalised recommendations